Sb3NetworkArchitectureArgs
Full path:
schola.scripts.sb3.settings.Sb3NetworkArchitectureArgs
schola.scripts.sb3.settings.Sb3NetworkArchitectureArgs
Sb3NetworkArchitectureArgs
Sb3NetworkArchitectureArgs(policy_parameters: 'Annotated[List[int], Parameter(consume_multiple=True)]' = <factory>, critic_parameters: 'Annotated[List[int], Parameter(consume_multiple=True)]' = <factory>, activation: 'ActivationFunctionEnum' = <ActivationFunctionEnum.ReLU: 'relu'>)Bases: object
Methods
| Item | Description |
|---|---|
| init | — |
Attributes
| Item | Description |
|---|---|
| activation | Activation function to use in the policy and critic networks. |
| policy_parameters | A list of layer widths representing the policy network architecture. |
| critic_parameters | A list of layer widths representing the critic (value function) network architecture. |
Parameters
policy_parameters (Annotated[List[int], Parameter(consume_multiple=True)])
critic_parameters (Annotated[List[int], Parameter(consume_multiple=True)])
activation (ActivationFunctionEnum)
init
__init__(policy_parameters=<factory>, critic_parameters=<factory>, activation=ActivationFunctionEnum.ReLU)Parameters
policy_parameters (Annotated[List[int], Parameter(consume_multiple=True)])
critic_parameters (Annotated[List[int], Parameter(consume_multiple=True)])
activation (ActivationFunctionEnum)
Returns
None
activation
= 'relu' activation: ActivationFunctionEnumActivation function to use in the policy and critic networks. This determines the non-linear activation function applied to each layer of the neural networks. The choice of activation function can affect the performance of the model and may depend on the specific characteristics of the environment.
critic_parameters
critic_parameters: Annotated[List[int], Parameter(consume_multiple=True)]A list of layer widths representing the critic (value function) network architecture. This defines the number of neurons in each hidden layer of the critic network. For example, [64, 64] would create a critic network with two hidden layers, each containing 64 neurons. This is only applicable for algorithms that use a critic (e.g., SAC). If set to None, it will use the default architecture defined by the algorithm.
policy_parameters
policy_parameters: Annotated[List[int], Parameter(consume_multiple=True)]A list of layer widths representing the policy network architecture. This defines the number of neurons in each hidden layer of the policy network. For example, [64, 64] would create a policy network with two hidden layers, each containing 64 neurons. If set to None, it will use the default architecture defined by the algorithm.